Project Summary: Comprehensive exposure assessments that account for mixtures of environmental chemical pollutants are vital to understand true relationships between human exposures and disease outcomes. Moreover, human or daily mobility of people is often misrepresented by exposure models resulting in exposure misclassification. This proposal aims to determine how air pollution chemical mixtures and human mobility impact environmental and human health risk assessments, which aligns with the NIEHS core mission ?to discover how the environment affects people in order to promote healthier lives.? The goals of the candidate are to gain training and research experience towards becoming an independent principal investigator, developing an extramurally funded research lab, and conducting research focused on spatiotemporal exposure and risk assessment modeling. The primary mentor, Dr. Kim Anderson, a professor at Oregon State University is an expert in passive exposure assessment methods and analytical quantification of chemical mixtures in environmental media, which provides an excellent environment to transition the candidate from a background in single-pollutant exposure assessment to multi-pollutant mixture exposure and risk assessment. Along with new teaching opportunities, the candidate will receive training from Dr. Anderson in research methods such as primary data collection, biochemical monitoring for epidemiological studies, and toxicology approaches in risk assessment. Collaborators Drs. Katrina Waters and Justin Teeguarden, senior scientists at Pacific Northwest National Laboratory, will provide career development advising and research training in areas such as data integration for epidemiology and toxicology studies and hands-on experience with large-scale computational resources. This proposal?s aims will address the following central hypotheses: (1) Accounting for chemical mixtures in exposure will produce synergistic health effects not observed by chemicals individually, and (2) Personal sampling and model-based exposure assessment accounting for human mobility will produce varying risk estimates depending on the pollutant and individuals? mobility. During the K99 phase, aim 1 will collect multi-chemical air quality data for a daily time resolved stationary monitoring campaign resulting in a space and time resolved multi-pollutant (Polycyclic aromatic hydrocarbons and volatile organic compounds) air quality dataset. Aim 2 will develop spatiotemporal exposure models for gas-phase mixtures using land use regression, geostatistical, and machine learning models. In the R00 phase, aim 3 will perform a risk assessment for chemical mixtures and acute lung health effects accounting for human mobility using a case-crossover design and comparing three exposure assessment methods: traditional spatiotemporal models, spatiotemporal models accounting for human mobility, and personal exposure monitors. Together, this proposal addresses the major limitations in environmental exposure assessment, pollutant mixtures and human mobility, and is within the mixtures and air pollution focus areas of environmental exposure research at NIEHS.